40 Hz Light Flicker Promotes Learning and Memory via Long Term Depression in Wild-Type Mice
Bibliographic record
Abstract
BACKGROUND: 40 Hz light flicker is a well-known non-invasive treatment that is thought to be effective in treating Alzheimer's disease. However, the effects of 40 Hz visual stimulation on neural networks, synaptic plasticity, and learning and memory in wild-type animals remain unclear. OBJECTIVE: We aimed to explore the impact of 40 Hz visual stimulation on synaptic plasticity, place cell, and learning and memory in wild-type mice. METHODS: c-Fos+ cell distribution and in vivo electrophysiology was used to explore the effects of 40 Hz chronic visual stimulation on neural networks and neuroplasticity in wild-type mice. The character of c-Fos+ distribution in the brain and the changes of corticosterone levels in the blood were used to investigate the state of animal. Place cell analysis and novel location test were utilized to examine the effects of 40 Hz chronic visual stimulation on learning and memory in wild-type mice. RESULTS: We found that 40 Hz light flicker significantly affected many brain regions that are related to stress. Also, 40 Hz induced gamma enrichment within 15 min after light flickers and impaired the expression of long-term potentiation (LTP), while facilitated the expression of long-term depression (LTD) in the hippocampal CA1. Furthermore, 40 Hz light flicker enhanced the expression of corticosterone, rendered well-formed place cells unstable and improved animal's learning and memory in novel local recognition test, which could be blocked by pre-treatment with the LTD specific blocker Glu2A-3Y. CONCLUSION: These finding suggested that 40 Hz chronic light flicker contains stress effects, promoting learning and memory in wild-type mice via LTD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".